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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 0-RES-JB
    6. 5986
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    Explanations

    mentions of the word "wer" with varying levels of activation

    oai_token-act-pair · gpt-3.5-turbo

    the word "wer" in various forms, signaling a focus on variations of that term

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     dogs
    -0.64
     ghosts
    -0.64
     PTSD
    -0.64
     accompanying
    -0.64
     Jinping
    -0.62
     makeup
    -0.62
     parenting
    -0.61
     esp
    -0.60
    âĹı
    -0.60
     paramedics
    -0.60
    POSITIVE LOGITS
    wer
    4.76
    WER
    1.65
    wered
    1.31
    wark
    1.18
     Wer
    1.14
    ws
    1.12
    swer
    1.11
    wen
    1.10
    wed
    1.04
    w
    1.04
    Activations Density 0.011%

    No Known Activations